A study of cart path planning based on the improvement of the elephant colony-ant colony algorithm

To solve the problem of imbalance between exploration and development of the ant colony algorithm, an improved algorithm for planning ant colony paths is proposed.First, the environment model is constructed by the raster method; second, the pheromone concentration in the ant colony algorithm is initialized by the best first search algorithm to prefetch suboptimal paths to improve the preconvergence speed of the algorithm; the parameters in the ant colony algorithm are optimized by the elephant swarm algorithm, so that the adjustment of the parameters can reduce the effect of the algorithm to improve the search performance in the ant colony algorithm.The ant colony algorithm was improved and simulation experiments were performed using Matlab to compare the results with the traditional ant colony algorithm. The experimental results show that the improved ACO algorithm has higher search efficiency and the number of iterations is reduced by almost 65%.